Hybrid Aluminium Metal Matrix Composites have gained a lot of attention in the industrial sphere due to their excellent mechanical properties and lightweight nature. However, machining these composites presents substantial challenges because of the variable mechanical properties across the bulk. Traditional machining, like drilling, calls for optimization of drilling parameters for ensuring high material removal rates (MRR), minimal surface roughness (Ra), and enhanced hole quality. This study employs Multi-Criteria Decision-Making (MCDM) techniques—MARCOS, MABAC, MOORA, WASPAS, and ARAS—combined with two distinct weighting strategies: Entropy and the Method of Removal Effects of Criteria (MEREC). Drilling of stir-cast hybrid aluminium composites (Al 7075 + SiC + fly ash + bagasse ash) was performed using Taguchi’s design of experiments. The MCDM techniques were then employed to obtain ranks of all the 27 experimental runs to choose the optimum. The results reveal that drill diameter and feed rate significantly influence optimal machining conditions. The study highlights that the 15th experimental run (10 mm drill diameter, 170 RPM spindle speed, 41 mm/min feed rate) yielded the best compromise across performance criteria. Furthermore, a strong correlation among rankings from different MCDM techniques demonstrates their robustness and reliability for machining optimization.
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